Offensive content is pervasive in social media and a reason for concern to companies and
government organizations. Several studies have been recently published investigating …

This paper describes the results of the shared tasks organized as part of the VarDial
Evaluation Campaign 2021. The campaign was part of the eighth workshop on Natural …

We create publicly available language identification (LID) datasets and models in all 22
Indian languages listed in the Indian constitution in both native-script and romanized text …

The massive spread of false information on social media has become a global risk
especially in a global pandemic situation like COVID-19. False information detection has …

Automatic socio-political and crisis event detection has been a challenge for natural
language processing as well as social and political science communities, due to the …

Language identification of social media text has been an interesting problem of study in
recent years. Social media messages are predominantly in code mixed in non-English …

This paper develops an approach to language identification in which the set of languages
considered by the model depends on the geographic origin of the text in question. Given that …

In this paper, we investigate the use of N-gram models and Large Pre-trained Multilingual
models for Language Identification (LID) across 11 South African languages. For N-gram …

Automatic speech recognition is being used everywhere these days. An essential part of this
is language identification. Our goal here is to identify the language of the media title, such as …

In recent years, the widespread use of social media has led to an increase in the generation
of toxic and offensive content on online platforms. In response, social media platforms have …